Eye to hand calibration using ANFIS for stereo vision-based object manipulation system

Standard industrial robot manipulator has possibility to manipulate the objects accurately in arbitrary position by using additional vision sensor. This applies in eye-to-hand camera configuration, where the stereo camera can cover the robot arm workspace and the object can be kept accurately for three dimension position estimation. The goal of this system is to control a robot arm to pick up and place the targeted object autonomously within its workspace. In order to accomplish this goal, a stereo vision technique including eye to hand calibration is applied. First, a stereo camera is calibrated to obtain the intrinsic and extrinsic camera parameters. Then, the specific color features of desired object are extracted using image processing algorithms. After that, based on centroid of desired object, 3D (3 dimension) position of the desired object is calculated. Then, camera and robot arm coordinate transformation was calibrated using adaptive artificial network based fuzzy interference system (ANFIS) method. Finally, the 3D coordinates of desired object are sent to robot arm controller as the inputs to move the end-effector equipped with gripper to the object location and pick up the object then place it to the desired location. The experiment was carried out using 6 DOF industrial robot arm and the results demonstrated the good performance of the system with acceptable errors.